class_docstr: An affine deterministic model.
docstr: Subset the model along the output dimension.
  
  Args:
      idcs: The output indices to subset the model to.
  
  Returns:
      The current model, subset to the specified output indices.
docstr_tok: ["Subset","the","model","along","the","output","dimension",".","Args",":","idcs",":","The","output","indices","to","subset","the","model","to",".","Returns",":","The","current","model",",","subset","to","the","specified","output","indices","."]
code: def subset_output(self, idcs: List[int]) -> AffineDeterministicModel:
      r"""Subset the model along the output dimension.
  
      Args:
          idcs: The output indices to subset the model to.
  
      Returns:
          The current model, subset to the specified output indices.
      """
      a_sub = self.a.detach()[..., idcs].clone()
      b_sub = self.b.detach()[..., idcs].clone()
      return self.__class__(a=a_sub, b=b_sub)
  
imports: from __future__ import annotations
  from abc import abstractmethod
  from typing import Callable, List, Optional, Union
  import torch
  from botorch.models.ensemble import EnsembleModel
  from botorch.models.model import Model
  from torch import Tensor
label_desc: Use image node_id 2 for calling the AffineDeterministicModel obj's underlying member method code with example usage: obj.subset_output(idcs) and returns: self